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在传统canny边缘检测的基础上,进一步进行自适应阈值的边缘检测方法的研究,比传统的方法有很大的优越性-Traditional canny edge detection on the basis of further adaptive threshold edge detection method, there are a lot of advantages than traditional methods
Date : 2025-12-22 Size : 858kb User : 陈婉

有关改良Canny算法的一些还算可以的文献-Improved Canny algorithm on some literature.
Date : 2025-12-22 Size : 1.72mb User : user

Article explaining Canny algorithm
Date : 2025-12-22 Size : 6.62mb User : Sezaru

Edge detection algorithms are important tools in image processing applications for carrying out much information and being relatively easy to produce. Sobel Canny and logarithmic algorithms [1] are among several edge detection algorithms used frequently nowadays. The ution of such edge detection algorithms is an old problem. Authors [1][3] tend to use visual uation that limits the comparison between different edge images. In this paper, we present a new edge enhancement method and five different measures that can be used to statistically uate edge detection algorithms. The new edge enhancement method is based on cooperation between different edge detection algorithms. The new edge preserves the advantages of each edge image. Experimental results using two edge detection algorithms proved the efficiency of this method.-Edge detection algorithms are important tools in image processing applications for carrying out much information and being relatively easy to produce. Sobel Canny and logarithmic algorithms [1] are among several edge detection algorithms used frequently nowadays. The ution of such edge detection algorithms is an old problem. Authors [1][3] tend to use visual uation that limits the comparison between different edge images. In this paper, we present a new edge enhancement method and five different measures that can be used to statistically uate edge detection algorithms. The new edge enhancement method is based on cooperation between different edge detection algorithms. The new edge preserves the advantages of each edge image. Experimental results using two edge detection algorithms proved the efficiency of this method.
Date : 2025-12-22 Size : 853kb User : sacoura
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